/Movie-Recommendation-System-Using-Feature-Extraction

Primary LanguageJupyter Notebook

Movie Recommendation System Using Feature Extraction

This is a movie recommendation system built using FEATURE EXTRACTION.

HOW DOES IT WORK?

The technique used to build this recommendation system is FEATURE EXTRACTION, which basically means all the necessary features shall be seperated and saved in a variable. Using TfidfVectorizer() the feature vectors are extracted and the cosine similarity is used to find the similarity between the user's search and these vectors.

OUTPUT

Result

Link to the tutorial for this project is : https://www.youtube.com/watch?v=7rEagFH9tQg&t=1097s